Evidence map›Paper›PMID 30302667›Full record

ArticleMedical & biological engineering & computing2019

Application of fractal theory and fuzzy enhancement in ultrasound image segmentation.

Zhemin Zhuang, Naihai Lei, Alex Noel Joseph Raj, Shunmin Qiu

Abstract read
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In one paragraph

Article in Medical & biological engineering & computing, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
1.5field-weighted citation impact, top 13% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed, 27 citations in OpenAlex.

  1. Real-time denoising of ultrasound images based on deep learning.Medical & biological engineering & computing · 2022
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors at 1 institution in 1 country.

Zhemin ZhuangDepartment of Electronic Engineering, Shantou University, Shantou, Guangdong, China.
Naihai LeiDepartment of Electronic Engineering, Shantou University, Shantou, Guangdong, China.
Alex Noel Joseph RajDepartment of Electronic Engineering, Shantou University, Shantou, Guangdong, China. jalexnoel@stu.edu.cn.ORCID http://orcid.org/0000-0003-1505-3159
Shunmin QiuImaging Department, First Hospital of Medical College of Shantou University, Shantou, Guangdong, China.
Shantou University · CN

Funding

Foundation of China 61471228Scientific Research Grant of Shantou University NTF17016the Key Project of Guangdong Province Science & Technology Plan 2015B020233018
6 · The paper itself

Abstract

The manuscript describes an ultrasound image segmentation technique based on the fractional Brownian motion (FBM) model. Here, the ultrasound images are first enhanced using a fuzzy-based technique, and later the FBM model is employed to obtain the fractal features used for segmentation. The novelty lies in combining the fuzzy-enhancement technique and FBM model, and further illustrating that fractal length-based segmentation provides better results than fractal dimension-based segmentation. Experimental results on ultrasound images of carotid artery clearly illustrate that the segmentation outputs obtained from fractal length are superior, and the high qualitative values of DSC, Precision, Recall and F

Indexed as

FractalsFuzzy LogicAlgorithmsCarotid ArteriesGallbladderHumansImage EnhancementLiverUltrasonographyFractal dimensionFractal lengthFractional Brownian motion (FBM)Fuzzy enhancementHurstSegmentation

Identifiers

PMID30302667
OpenAlexW2896124416

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.